Effects of Lower Limb Heat Therapy, Exercise Training, or a Combined Intervention on Vascular Function: A Randomized Controlled Trial
Bibliographic record
Abstract
PURPOSE: The purpose of this study is to compare the effects of 8 wk of no intervention (CON), lower limb heat therapy (HEAT), moderate-intensity exercise training (EX), or combined training and therapy (HEATEX) in young, healthy recreationally active adults. METHODS: Sixty participants (23 ± 3 yr, 30 females) were randomly allocated into CON ( n = 15), HEAT ( n = 15), EX ( n = 14), or HEATEX ( n = 16). The primary outcome was vascular function, assessed through brachial artery flow-mediated dilation tests. Secondary measures included arterial stiffness (pulse wave velocity), cardiorespiratory fitness (V̇O 2peak ), body composition, and quadriceps muscle strength. RESULTS: There were no differences in brachial artery flow-mediated dilation between the groups before and after the interventions (all P > 0.05). Both interventions with a heating component were associated with within-group reductions in carotid-femoral pulse wave, and increase in absolute and relative V̇O 2peak after 8 wk (HEAT: ∆-0.27 [-0.53, -0.02] m s -1 , ∆0.18 [0.06, 0.29] L·min -1 , ∆2.18 [0.60, 3.76] mL·kg -1 ·min -1 , respectively; HEATEX: ∆-0.33 [-0.58, -0.09], ∆0.21 [0.11, 0.32] L·min -1 , ∆2.59 [1.06, 4.12] mL·kg -1 ·min -1 , respectively), but no between-group differences were observed ( P = 0.25, P = 0.21, and P = 0.55, respectively). There was also a within-group decrease in body fat percentage with EX (∆-1.37 [-2.45, -0.29] %), but no changes in leg strength in any of the groups ( P = 0.79). CONCLUSIONS: This randomized controlled trial is the first to examine the efficacy of lower limb heating against traditionally prescribed exercise training. In our young cohort, 8 wk of training and/or therapy was insufficient to improve vascular function. More intense protocols and longer interventions involving lower limb heating may be required to elicit improvements in health outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".